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Computer Vision Projects with OpenCV and Python 3

You're reading from   Computer Vision Projects with OpenCV and Python 3 Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789954555
Length 182 pages
Edition 1st Edition
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Author (1):
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Matthew Rever Matthew Rever
Author Profile Icon Matthew Rever
Matthew Rever
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Table of Contents (9) Chapters Close

Preface 1. Setting Up an Anaconda Environment 2. Image Captioning with TensorFlow FREE CHAPTER 3. Reading License Plates with OpenCV 4. Human Pose Estimation with TensorFlow 5. Handwritten Digit Recognition with scikit-learn and TensorFlow 6. Facial Feature Tracking and Classification with dlib 7. Deep Learning Image Classification with TensorFlow 8. Other Books You May Enjoy

Handwritten Digit Recognition with scikit-learn and TensorFlow

In this chapter, we are going to learn how machine learning can be applied to computer vision projects, using a couple of different Python modules. We will also create and train a support vector machine that will actually perform our digit classification.

In this chapter, we will be covering the following topics:

  • Acquiring and processing MNIST digit data
  • Creating and training a support vector machine
  • Applying the support vector machine to new data
  • Introducing TensorFlow with digit classification
  • Evaluating the results
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